Abstract
For a wide class of applications referred to as indirect-sensing experiments, a systematic approach yielding solutions in recursive form is established. Indirectsensing experiments include problems of estimation, filtering, system identification, and interpolation and smoothing by splines. Our approach is based on the novel notion of a discrete-time generalized (not necessarily stochastic) innovations process. The discrete-time linear least-squares filtering problem is used to relate the new concept to the familiar one of a stochastic innovations process. An application to the problem of identifying recursively impulse responses and system parameters by using pseudorandom binary sequences as probing inputs is considered. Further, the problem of interpolation and smoothing by splines is approached by the method developed.
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Mosca, E. (1975). Recursive solutions to indirect sensing measurement problems by a generalized innovations approach. In: Marchuk, G.I. (eds) Optimization Techniques IFIP Technical Conference Novosibirsk, July 1–7, 1974. Optimization Techniques 1974. Lecture Notes in Computer Science, vol 27. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-07165-2_11
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DOI: https://doi.org/10.1007/3-540-07165-2_11
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